Pneumatic conveying system and method using optical flow characterization data

ABSTRACT

A method includes optically interacting a flow of bulk material or powder in a pneumatic conveyor with an integrated computational element (“ICE”) configured to modify an electromagnetic radiation according to a characteristic of the flow of bulk material or powder. The method includes detecting the modified electromagnetic radiation with a detector, producing an output signal corresponding to the characteristic of the flow, and receiving and processing the output signal with a signal processor to yield a value for the characteristic of the flow. Also, the method includes modifying at least one of a flow rate or an air pressure in the pneumatic conveyor in response to the value of the characteristic of the flow. The bulk material or powder includes a dry cement or a dry cement component.

BACKGROUND

The exemplary embodiments described herein relate to optical computingdevices and methods for measuring characteristics of a dry bulk materialor powder. More particularly, embodiments disclosed herein relate tosystems and methods for measuring the characteristics of a flowing bulkmaterial or powder and use the measurements to improve flowcharacteristics.

Some industrial applications that use bulk materials and powders includeforming set cement compositions for the construction industry. The oiland gas industry also uses set cement compositions for stabilizing andplugging wellbores, among other purposes. The operational parametersrelating to cement slurries and the characteristics of the resultant setcement derive, at least in part, from the dry cement composition and thecomposition and concentration of the optional cement slurry additivesmixed as powders in the dry cement blend composition.

Accordingly, while storing and conveying raw materials used in a blendto form a dry cement, it is desirable to have a correct determination ofthe raw materials used and their physical and chemical condition duringstorage and transfer. It is also desirable to determine flow conditionsin a conveying system to optimize energy costs and to avoid damage tothe infrastructure for handling the materials. Current techniquesinclude discrete measurements in storage containers and pipelines atspecific locations and times. Other techniques involve imprecise andunreliable methods such as detecting the sound that the raw materialmakes as it travels through the pipelines. Other approaches includeanalyzing the discharge of the raw material at the end or at someintermediate point of the pipeline.

These measurement techniques typically involve a complicated, multi-stepprocess of mixing harsh chemicals with the bulk materials or powders andanalyzing the products via expensive, time-consuming methods like x-raydiffraction, gravimetric analysis, slurrying and testing viscosity overtime in specified temperature and pressure conditions and the like.Moreover, these measurement techniques may be insufficient for takingremedial action when an error occurs with one or more of the materialsupplies and an entire batch of dry cement is lost or deployed onlocation without satisfying quality standards. In relation to downholeoil and gas operations, improperly deployed cementing operations canincrease both costs and liabilities, including costly remedialoperations to repair the set cement.

BRIEF DESCRIPTION OF THE DRAWINGS

The following figures are included to illustrate certain aspects of theexemplary embodiments described herein, and should not be viewed asexclusive embodiments. The subject matter disclosed is capable ofconsiderable modifications, alterations, combinations, and equivalentsin form and function, as will occur to those skilled in the art andhaving the benefit of this disclosure.

FIG. 1 illustrates an exemplary integrated computational element (ICE),according to one or more embodiments.

FIG. 2 illustrates a block diagram non-mechanistically illustrating howan optical computing device distinguishes electromagnetic radiationrelated to a characteristic of interest from other electromagneticradiation, according to some embodiments.

FIG. 3 illustrates an exemplary system for monitoring a dry cementpresent in a container, according to some embodiments.

FIG. 4 illustrates an exemplary housing that may be used to house anoptical computing device, according to some embodiments.

FIG. 5 illustrates a system for storing and conveying raw materials fromstorage containers to transportation units including an opticalcomputing device, according to some embodiments.

FIG. 6 illustrates a conveyor in a pneumatic conveying system usingoptical flow characterization data obtained with an optical computingdevice, according to some embodiments.

FIG. 7 illustrates a flowchart including steps in a method for operatinga pneumatic conveying system using optical flow characterization data,according to some embodiments.

DETAILED DESCRIPTION

The exemplary embodiments described herein relate to optical computingdevices and methods for monitoring bulk materials or powders and, inparticular, to systems and methods for determining the flowcharacteristics and condition of bulk materials or powders. Methods andsystems consistent with the present disclosure are able to characterizethe flow by “seeing” the bulk materials or powders as they flow througha conveying system in real time. Accordingly, methods and systemsconsistent with the present disclosure enable adjustment of conveyingairflow rates based on the instantaneous characterization of materialflow through the system.

Many industrial applications commonly use dry bulk materials andpowders. For example, the agro-industry, the food industry, and thepharmaceutical industry process large amounts of grains, powders,liquids and small unit sizes (fruits such as grapes, raisins, and nuts,medications in the form of pills) for storage, packaging, anddistribution. Industrial applications of dry bulk materials or powdersinclude storing separated raw materials under dry conditions prior tomixing and preparation for use. Industrial applications of dry bulkmaterials typically include systems and methods to store the rawmaterials in separate containers for each raw material and conveyingmechanisms to transport the raw materials from storage containers to ascale tank and from the scale tank to a shipping location, or adeployment location. At each of the storage and conveying stages, it isdesirable to have a precise knowledge of the type and physical conditionof the material handled. Some of the characteristics that are relevantin many applications include powder particle size, moisture content,homogeneity of a mixture, and flow conditions in a conveying system.

The oil and gas industry uses bulk materials and powders for makingcement blends deployed, for example, to plug boreholes or secure casingstrings therein. Some of these cementing projects may be quitechallenging, as it may be desirable to convey a cement compositionbeyond the ocean floor, several thousand feet underneath the watersurface. Accordingly, it is desirable to verify the correct dry cementblend prior to deploying the cement in the field. The oil and gasindustry uses many types of cements according to different desirablecharacteristics for specific applications. In some instances, drycements include any one of the raw materials used in Portland cements,gypsum cements, hydraulic cements and Sorel cements. Other dry materialsbesides dry cement typically used in the oil and gas industry includesalt, lime, sand, POZMIX®, and the like. An accurate account of theidentity and condition of the raw materials used to prepare the cementmix during storage and conveying of the raw materials is thereforehighly desirable. In some instances, the physical condition is relevantto reactivity of the raw material in cement slurries. For example, fines(reduced size particles) react differently from coarser particles of thesame material. Moreover, coarse materials have a tendency to settle anddeposit in storage containers and transfer tubes before arriving to thedesired destination, reducing material transfer efficiency. Furthermore,blending conditions may change in time, and thus it is desirable to havea sense of the condition of the bulk material or powder being used inreal time, and adapt the blending methodology accordingly.

Current attempts to obtain information about bulk material or powderidentity and condition include sample extraction and analysis on aperiodical basis at multiple locations. These methods can be timeconsuming and discrete in nature, providing partial and extemporaneousinformation that may not be sufficient for a timely remedial action.Thus, when an error occurs in the supply logistics and the wrongmaterial is used, or pipeline corrosion contaminates the sample or themixture, or an air pump or compressor leaks moisture into the system, anentire batch of the mix may be compromised. This may result in the lossof the batch, or in a worst-case scenario, more serious damage can occurwhen the wrong batch deploys to the field. Such may be the situationwhen a compromised cement mix is used in structural engineering, such asplugging or lining a wellbore extending from the sea bed thousands offeet under water.

The exemplary systems and methods described herein employ variousconfigurations of optical computing devices, also commonly referred toas “opticoanalytical devices,” for the rapid analysis of dry cements.The disclosed systems and methods may be suitable for use in the oil andgas industry since the described optical computing devices provide acost-effective, rugged, and accurate means for identifying bulkmaterials and powders in order to facilitate the effective production ofcement slurries and set cements in oil/gas applications. It will beappreciated, however, that the various disclosed systems and methods areequally applicable to other technology fields including, but not limitedto, the food and drug industry, industrial applications, miningindustries, or any field where it may be advantageous to determine inreal-time or near real-time a characteristic of a dry composition,especially to determine the quality of the dry composition and of eachof its components.

The optical computing devices disclosed herein, which are described inmore detail below, can advantageously provide rapid analysis of at leastone characteristic of a dry cement (e.g., the composition of individualcomponents in the dry cement or the particle size distribution in thedry cement). As described above, such a detailed analysis currentlyrequires extensive time, high cost, and harsh chemicals and can giveunreliable results. By contrast, the optical computing devices disclosedherein may provide rapid analysis of dry cements with minimal sampleprep, if any. Additionally, because the analysis is rapid, multiplemeasurements may be obtained to reduce error. Further, because of thesmall size and relatively low cost of the optical computing devicesdisclosed herein, the methods for analyzing dry cements are suitable notonly for laboratory use, but also, in-field analysis (e.g., at amanufacturing or mining site, at a distribution center, or at a wellsite).

A significant and distinct advantage of the optical computing devicesdisclosed herein is that they can be configured to specifically detectand/or measure a particular characteristic of interest of a dry cement,thereby allowing qualitative and/or quantitative analyses of thematerial of interest to occur without having to undertake atime-consuming sample processing procedure. With rapid analysescapabilities on hand, the exemplary systems and methods described hereinmay be able to determine the identity and flow characteristics of rawmaterials used to form dry cement compositions.

As used herein, the term “dry cement” refers to a mixture of solidparticles including at least some cement particles and is not hydratedbeyond ambient conditions (e.g., no additional water has been added). Itshould be noted that the term “dry cement” does not refer to set cements(e.g., that have been formed from a cement slurry).

Dry cements may comprise a single cement or comprise a blend of two ormore cements. Examples of dry cements may include, but are not limitedto, hydraulic cements, Portland cement, gypsum cements, pozzolancements, calcium phosphate cements, high alumina content cements, silicacements, high alkalinity cements, shale cements, acid/base cements,magnesia cements (e.g., Sorel cements), zeolite cement systems, cementkiln dust cement systems, slag cements, micro-fine cements, bentonites,and the like, any derivative thereof, and any combination thereof.Examples of Portland cements may include, but are not limited to,Portland cements classified as Classes A, C, H, and G according to APIand their equivalent, Ordinary Portland cements of Type I, I/II, III,and V according to ASTM, including combinations thereof. Examples ofpozzolan cements may include, but are not limited to, fly ash, silicafume, granulated blast furnace slag, calcined shale, opaline shale,pumice, pumicite, diatomaceous earth, volcanic ash, tuft, cement kilndust, and any combination thereof.

As used herein, the term “characteristic” refers to a chemical,mechanical, or physical property (quantitative or qualitative) of amaterial of interest (e.g., a dry cement or an analyte thereof). As usedherein, the term “analyte” refers to a chemical component. The termanalyte encompasses chemical components that are at least one of:present in the material of interest, may be added to the material ofinterest, involved in a chemical reaction (e.g., reagents and products)transpiring within the material of interest, and not involved in achemical reaction transpiring within the material of interest.Illustrative characteristics of a material of interest that can bemonitored with the optical computing devices disclosed herein caninclude, for example, chemical composition (e.g., identity andconcentration in total or of individual analytes), contaminant content,pH, viscosity, density, ionic strength, salt content, porosity, opacity,bacteria content, particle size distribution, color, temperature,hydration level, oxidation state, and the like. Moreover, the phrase“characteristic of interest” may be used herein to refer to acharacteristic of a material of interest.

Examples of analytes within a dry cement may include, but are notlimited to, SiO₂, Al₂O₃, FeO, Fe₂O₃, CaO, Na₂O, K₂O, MgO, SO₃, Mn₂O₃,TiO₂, P₂O₅, SnO, SrO, (CaO)₃.SiO₂, (CaO)₂.SiO₂, (CaO)₃.Al₂O₃,(CaO)₃.Al₂O₃.Fe₂O₃, CaSO₄.H₂O, SO₃, Ca(OH)₂, Al(OH)₄ ⁻, H₄SiO₄, freelime, inorganic salts (e.g., sodium, potassium, magnesium, and calciumsalts of sulfate, phosphate, and carbonate), metal containing compounds(e.g., bromide, chloride, nitrate, sulfate, and phosphate salts ofcadmium, zinc, nickel, copper, lead, and the like, metal oxides of suchmetals, and the like), hydroxides, water, and any combination thereof.

In some instances, the foregoing analytes may be used in classifyingcements (i.e., as a major component) or as grading cements (i.e., as aminor components), which depends on the dry cement. As used herein, the“major component” of a dry cement refers to a component or analyte thatidentifies the type of dry cement (e.g., Portland cement versus Sorelcement or Type I Portland cement versus Type V Portland cement). As usedherein, the “minor component” of a dry cement refers to a component oranalyte that is not a major component. The terms “major component” and“minor component” do not necessarily relate to a concentration. Forexample, in Ordinary Grade, Class G Portland cement may have about 5%CaO₃.Al₂O₃ as one of the major components and up to about 6% MgO as oneof the minor components.

As used herein, the term “cement slurry additive” refers to an additivethat can be included in a cement slurry with water and a dry cement.Cement slurry additives may be liquids or dry additives (e.g., powders).In some instances, the dry cement and at least one cement slurryadditive (typically a dry additive) may be combined to form a mixturethat can be used in preparing a cement slurry. The mixture may beprepared at a storage facility, manufacturing facility, laboratory,distribution center, at the well site, or in transit between any ofthese locations.

Examples of cement slurry additives may include, but are not limited to,set retarders, set accelerators, fillers (e.g., weighting agents,lightweight particles like glass beads, rubber particles, and the like),dispersants, gelling agents, and the like, and any combination thereof.

As used herein, the term “electromagnetic radiation” refers to radiowaves, microwave radiation, infrared and near-infrared radiation,visible light, ultraviolet light, X-ray radiation and gamma rayradiation.

As used herein, the term “optical computing device” refers to an opticaldevice that receives an input of electromagnetic radiation from asubstance or sample of the substance, and produces an output ofelectromagnetic radiation from a processing element arranged within theoptical computing device. The processing element may be, for example, anintegrated computational element (ICE) used in the optical computingdevice. As discussed in detail below, the ICE optically interacts andchanges the electromagnetic radiation incident on a detector such thatan output of the detector can be correlated to at least onecharacteristic of the substance being measured or monitored. The outputof electromagnetic radiation from the processing element can bereflected electromagnetic radiation, transmitted electromagneticradiation, and/or dispersed electromagnetic radiation. Whether thedetector analyzes reflected or transmitted electromagnetic radiation maydepend on the structural parameters of the optical computing device aswell as other considerations known to those skilled in the art. Inaddition, emission and/or scattering by the substance, for example viafluorescence, luminescence, Raman scattering, and/or Raleigh scattering,can also be monitored by the optical computing devices.

As used herein, the term “optically interact” or variations thereofrefers to the reflection, transmission, scattering, diffraction, orabsorption of electromagnetic radiation either on, through, or from oneor more processing elements (i.e., integrated computational elements).Accordingly, optically interacted light refers to electromagneticradiation that has been reflected, transmitted, scattered, diffracted,or absorbed by, emitted, or re-radiated, for example, using theintegrated computational elements, but may also apply to interactionwith a dry cement.

The exemplary systems and methods described herein will include at leastone optical computing device configured to measure at least onecharacteristic of a dry cement or analyte thereof. In some embodiments,the optical computing devices suitable for use in the exemplaryembodiments described herein may be mobile or portable. In someembodiments, the optical computing devices suitable for use in theexemplary embodiments described herein may be a portion of tank, silo,vat, pipeline, tube, or the like that store, mix, transfer or otherwisecontain or transport dry cement (e.g., within a wall).

The presently described optical computing devices combine the advantageof the power, precision, and accuracy associated with laboratoryspectrometers, while being extremely rugged and suitable for field use.Furthermore, the optical computing devices can perform calculations inreal-time or near real-time without the need for time-consuming sampleprocessing. In this regard, in some embodiments the optical computingdevices detect and analyze particular characteristics of interest. As aresult, interfering signals are discriminated from those of interest byappropriate configuration of the optical computing devices, such thatthe optical computing devices provide a rapid response regarding thecharacteristic of interest as based on the detected output. In someembodiments, the detected output is a voltage indicative of themagnitude of the characteristic of interest. The foregoing advantagesand others make the optical computing devices particularly well suitedfor field use.

In some embodiments, the optical computing devices detect not only thecomposition and concentrations of an analyte in a material of interest,but also determine physical properties and other characteristics of thematerial of interest as well, based on their analysis of theelectromagnetic radiation received from the substance. For example, theoptical computing devices can determine the concentration of an analyteand correlate the determined concentration to a characteristic of thematerial of interest by using suitable processing means. In someembodiments, optical computing devices as disclosed herein provide ameasurement of a granularity of a powder sample, or an average particlesize in the powder sample. As will be appreciated, the optical computingdevices can detect as many characteristics as desired for a givenmaterial of interest. All that is required to accomplish the monitoringof multiple characteristics of interest is the incorporation of suitableprocessing and detection means within the optical computing device foreach characteristic of interest (e.g., the concentration of an analyte,the particle size distribution, or the temperature). Another property ofa dry cement that can be measured may be the particle size of thedifferent components in the cement.

In some embodiments, the properties of the material of interest can bedetermined using a combination of characteristics of interest (e.g., alinear, non-linear, logarithmic, and/or exponential combination).Accordingly, the more characteristics detected and analyzed using theoptical computing devices, the more accurately the properties of thematerial of interest will be determined. For example, properties of adry cement that may be determined using optical computing devicesdescribed herein may include, but are not limited to, the absoluteconcentration of an analyte, the relative ratios of two or moreanalytes, the presence or absence of an analyte, and the like, and anycombination thereof.

Optical computing devices as described herein utilize electromagneticradiation to perform calculations, as opposed to the hardwired circuitsof conventional electronic processors. When electromagnetic radiationinteracts with a material of interest, unique physical and chemicalinformation about the material of interest may be encoded in theelectromagnetic radiation that is reflected from, transmitted through,or radiated from the material of interest. This information is thespectral “fingerprint” of the material of interest. The opticalcomputing devices described herein are capable of extracting theinformation of the spectral fingerprint of multiple characteristics of amaterial of interest (e.g., a dry cement blend or an analyte thereof),and converting that information into a detectable output regarding theoverall properties of the monitored material of interest. That is,through suitable configurations of the optical computing devices,electromagnetic radiation associated with characteristics of interestcan be separated from electromagnetic radiation associated with allother components of the material of interest in order to estimate theproperties (e.g., reactivity) of the monitored substance (e.g., a drycement blend or an analyte thereof) in real-time or near real-time.

Each of the ICEs used in the exemplary optical computing devicesdescribed herein is capable of distinguishing electromagnetic radiationrelated to the characteristic of interest from electromagnetic radiationrelated to other components of a dry cement blend.

A method according to embodiments disclosed herein includes opticallyinteracting a flow of bulk material or powder in a pneumatic conveyorwith an ICE configured to detect a characteristic of the flow. Themethod also includes generating an output signal corresponding to thecharacteristic of the flow detected by the ICE and receiving andprocessing the output signal with a signal processor to yield a valuefor the characteristic of the flow. Further, in some embodiments themethod includes modifying at least one of a flow rate or an air pressurein the pneumatic conveyor in response to the value of the characteristicof the flow.

A device according to some embodiments includes a processor circuit anda memory circuit storing commands, which, when executed by the processorcircuit, cause the device to perform a method including receiving afirst signal from a first optical computing device at a first locationin a system for storing and conveying materials. The commands also causethe device to perform the step of receiving a second signal from asecond optical computing device at a second location in the system forstoring and conveying materials. The first and second signals resultfrom electromagnetic radiation interacted with a bulk material or apowder flowing in a transfer tube, and at least one of the first andsecond signals results from electromagnetic radiation modified by an ICEaccording to a characteristic of the flow of bulk material or powder. Insome embodiments, the commands also cause the device to perform the stepof determining from the first and second signal a characteristic of theflow of the bulk material or powder along the transfer tube. Bulkmaterials or powders as disclosed herein may include not only drycement, but also may include dry barite powders and blends used fordrilling fluids. More generally, bulk materials or powders as disclosedherein include dry powders and blends such as fertilizers,pharmaceuticals and agro-industrial products.

A method as disclosed herein includes receiving an output signal fromeach of a plurality of optical computing devices disposed in separatelocations in a pneumatic conveyor including a flowing bulk material orpowder. In some embodiments, the method includes processing each of theoutput signals from the plurality of optical computing devices with asignal processor and determining a characteristic of the flow based onthe processing of the output signals. Further, in some embodiments themethod includes modifying a characteristic of the pneumatic conveyor inresponse to the value of characteristic of the flow.

FIG. 1 illustrates an exemplary ICE 100 suitable for use in the opticalcomputing devices used in systems and methods described herein. Asillustrated, ICE 100 may include a plurality of alternating layers 102and 104, such as silicon (Si) and SiO₂ (quartz), respectively. Ingeneral, these layers 102, 104 consist of materials whose index ofrefraction is high and low, respectively. Other examples might includeniobia and niobium, germanium and germania, MgF, SiO_(x), and other highand low index materials known in the art. An optical substrate 106provides support to layers 102, 104, according to some embodiments. Insome embodiments, optical substrate 106 is BK-7 optical glass. In otherembodiments, optical substrate 106 may be another type of opticalsubstrate, such as quartz, sapphire, silicon, germanium, zinc selenide,zinc sulfide, or various plastics such as polycarbonate,polymethylmethacrylate (PMMA), polyvinylchloride (PVC), diamond,ceramics, combinations thereof, and the like.

At the opposite end (e.g., opposite optical substrate 106 in FIG. 1),ICE 100 may include a layer 108 that is generally exposed to theenvironment of the device or installation. The number of layers 102, 104and the thickness of each layer 102, 104 are determined from thespectral attributes acquired from a spectroscopic analysis of acharacteristic of interest using a conventional spectroscopicinstrument. The spectrum of interest of a given characteristic ofinterest typically includes any number of different wavelengths. Theexemplary ICE 100 in FIG. 1 does not in fact represent any particularcharacteristic of interest, but is provided for purposes of illustrationonly. Consequently, the number of layers 102, 104 and their relativethicknesses, as shown in FIG. 1, bear no correlation to any particularcharacteristic of interest. Nor are layers 102, 104 and their relativethicknesses necessarily drawn to scale, and therefore should not beconsidered limiting of the present disclosure. Moreover, those skilledin the art will readily recognize that the materials that make up eachlayer 102, 104 (i.e., Si and SiO₂) may vary, depending on theapplication, cost of materials, and/or applicability of the materials tothe monitored substance.

In some embodiments, the material of each layer 102, 104 can be doped ortwo or more materials can be combined in a manner to achieve the desiredoptical characteristic. In addition to solids, ICE 100 may also containliquids and/or gases, optionally in combination with solids, in order toproduce a desired optical characteristic. In the case of gases andliquids, ICE 100 can contain a corresponding vessel (not shown), whichhouses gases or liquids. Exemplary variations of ICE 100 may alsoinclude holographic optical elements, gratings, piezoelectric, lightpipe, digital light pipe (DLP), variable optical attenuators, and/oracousto-optic elements that, for example, can create transmission,reflection, and/or absorptive properties of interest.

Layers 102, 104 exhibit different refractive indices. By properlyselecting the materials of layers 102, 104, their relative thicknessesand spacing ICE 100 may be configured to selectivelypass/reflect/refract predetermined fractions of electromagneticradiation at different wavelengths. Each wavelength is given apredetermined weighting or loading factor. The thickness and spacing oflayers 102, 104 may be determined using a variety of approximationmethods from the spectrograph of the characteristic of interest. Thesemethods may include inverse Fourier transform (IFT) of the opticaltransmission spectrum and structuring ICE 100 as the physicalrepresentation of the IFT. The approximations convert the IFT into astructure based on known materials with constant refractive indices.

The weightings that layers 102, 104 of ICE 100 apply at each wavelengthare set to the regression weightings described with respect to a knownequation, or data, or spectral signature. Briefly, ICE 100 may beconfigured to perform the dot product of the input light beam into ICE100 and a desired loaded regression vector represented by each layer102, 104 for each wavelength. As a result, the output light intensity ofICE 100 is related to the characteristic of interest.

FIG. 2, illustrates a block diagram that non-mechanistically illustrateshow an optical computing device 200 is able to distinguishelectromagnetic radiation related to a characteristic of interest fromother electromagnetic radiation. As shown in FIG. 2, illumination byincident electromagnetic radiation induces an output of electromagneticradiation from a bulk material or powder 202 (e.g., sample-interactedlight), some of which is electromagnetic radiation 204 corresponding tothe characteristic of interest and some of which is backgroundelectromagnetic radiation 206 corresponding to other characteristics ofthe bulk material or powder 202. In some embodiments, bulk material orpowder 202 may include one or more characteristics of interest that maycorrespond to the one or more analytes of bulk material or powder 202.

Although not specifically shown, one or more processing elements may beemployed in the optical computing device 200 in order to restrict theoptical wavelengths and/or bandwidths of the system and therebyeliminate unwanted electromagnetic radiation existing in wavelengthregions that have no importance. Such processing elements can be locatedanywhere along the optical train, such as directly after a light source,which provides the initial electromagnetic radiation.

Beams of electromagnetic radiation 204 and 206 impinge upon the opticalcomputing device 200, which contains an exemplary ICE 208 therein. Inthe illustrated embodiment ICE 208 may produce optically interactedlight, for example, transmitted optically interacted light 210, andreflected optically interacted light 214. In operation, ICE 208 may beconfigured to distinguish electromagnetic radiation 204 from backgroundelectromagnetic radiation 206.

Transmitted optically interacted light 210, which may be related to thecharacteristic of interest of the bulk material or powder 202, may beconveyed to a detector 212 for analysis and quantification. In someembodiments, detector 212 produces an output signal in the form of avoltage that corresponds to the particular characteristic of bulkmaterial or powder 202. In at least one embodiment, the signal producedby detector 212 and the characteristic of bulk material or powder 202(e.g., concentration of an analyte, or flow speed) may be directlyproportional. In other embodiments, the relationship may be a polynomialfunction, an exponential function, and/or a logarithmic function. Thereflected optically interacted light 214 may be related to othercharacteristics of the bulk material or powder 202, and can be directedaway from detector 212. In alternative configurations, ICE 208 is suchthat reflected optically interacted light 214 relates to thecharacteristic of interest, and the transmitted optically interactedlight 210 relates to other characteristics in the bulk material orpowder 202.

In some embodiments, a second detector 216 can be present and arrangedto detect the reflected optically interacted light 214. In otherembodiments, second detector 216 may be arranged to detectelectromagnetic radiation 204 and 206 derived from the bulk material orpowder 202 or electromagnetic radiation directed toward or before thebulk material or powder 202. Without limitation, second detector 216 maybe used to detect radiating deviations stemming from an electromagneticradiation source (not shown), which provides the electromagneticradiation (i.e., light) to the device 200. For example, radiatingdeviations can include such things as, but not limited to, intensityfluctuations in the electromagnetic radiation, interference fluctuations(e.g., dust or other interferences passing in front of theelectromagnetic radiation source), coatings on windows included withoptical computing device 200, combinations thereof, or the like. In someembodiments, a beam splitter (not shown) splits electromagneticradiation 204 and 206, and the transmitted or reflected electromagneticradiation can then be directed to two or more ICEs 208. That is, in suchembodiments, the transmitted or reflected electromagnetic radiationpasses through ICE 208, which performs the computation before it travelsto detector 212.

The characteristic(s) of interest being analyzed using optical computingdevice 200 can be further processed and/or analyzed computationally toprovide additional characterization information about bulk material orpowder 202, or an analyte thereof. In some embodiments, theidentification and concentration of each analyte of interest in bulkmaterial or powder 202 can be used to predict certain physicalcharacteristics of a resulting dry cement combination. For example, thebulk characteristics of the dry cement (e.g., reactivity, set time, andthe like) can be estimated by using a combination of the propertiesconferred to the dry cement by each of the bulk material or powder 202used in a cement blend. For example, the relative ratios of some of theanalytes can indicate a concentration or range of concentration ofcement slurry additives that should be used in preparing a cement slurryfrom bulk material or powder 202.

In some embodiments, knowledge of the composition and concentration ofraw materials prevents a reduction in the quality of the dry cement. Insome instances, mixing the stored dry cement with one or more other drycements may achieve a desired classification or grade of dry cement. Byway of non-limiting example, lime can degrade over time with exposure tocarbon dioxide. Accordingly, lime is an analyte of interest that may bemonitored or measured in bulk material or powder 202, according to someembodiments.

Some embodiments use a computer algorithm to estimate the impact of acertain material quality or a certain flow characteristic in bulkmaterial or powder 202 on the final cement composition. The algorithmmay be part of an artificial neural network configured to use theconcentration of each characteristic of interest in order to evaluatethe overall characteristic(s) of the dry cement composition and predictthe composition and/or concentration of the cement slurry additivesincluded to provide for desired properties in resultant cement slurries.An artificial neural network can be trained using samples ofpredetermined characteristics of interest, and thereby generating avirtual library. As the virtual library available to the artificialneural network becomes larger, the neural network can become morecapable of accurately predicting the characteristic of interestcorresponding to a bulk material or powder or analyte thereof.Furthermore, with sufficient training, the artificial neural network canmore accurately predict the characteristics of the dry cementcombination, even in the presence of unknown analytes.

In some embodiments, data collected using the optical computing devicecan be archived along with data associated with operational parametersbeing logged at a job site. Evaluation of job performance allowsimprovement of future operations and the planning of remedial action, ifdesired. In addition, the data and information can be communicated(wired or wirelessly) to a remote location by a communication system(e.g., satellite communication or wide area network communication) forfurther analysis. Automated control with a long-range communicationsystem can further facilitate the performance of remote job operations.In particular, an artificial neural network facilitates the performanceof remote job operations. In other embodiments, however, remote joboperations can occur under direct operator control, where the operatoris not at the job site (e.g., via wireless technology).

FIG. 3 illustrates an exemplary system 300 for monitoring a bulkmaterial or powder 302, according to one or more embodiments. In theillustrated embodiment, bulk material or powder 302 may be containedwithin a container 304. In at least one embodiment, container 304 may bea scale tank that actively mixes bulk material or powder 302 presenttherein into a cement composition while system 300 collectsmeasurements. In at least one embodiment, container 304 may be a cup orthe like of a transport unit, such as a truck or a boat. In otherembodiments container 304 may be any other type of container, asgenerally described or otherwise defined herein. For example, container304 may be a storage vessel or silo, or a pipeline such as a transfertube used in the oil and gas industry, e.g., in a pneumatic conveyingsystem.

System 300 may include at least one optical computing device 306, whichmay be similar in some respects to optical computing device 200 of FIG.2. While not shown, device 306 may be housed within a casing or housingconfigured to substantially protect the internal components of device306 from damage or contamination from the external environment. Thehousing may couple device 306 to container 304 mechanically withmechanical fasteners, threads, brazing or welding techniques, adhesives,magnets, combinations thereof or the like.

As described in detail below, optical computing device 306 may be usefulin determining a particular characteristic of bulk material or powder302 within container 304, such as determining a concentration of ananalyte present within bulk material or powder 302.

Knowing at least some of the characteristics of bulk material or powder302 may help determine the overall composition of the bulk material orpowder 302. Knowing the composition of bulk material or powder 302allows for a more accurate determination of the composition and/orconcentration of cement slurry additives to use in subsequent cementslurries. In turn, the cementing operation that utilized the cementslurry mitigates premature setting or delayed setting. Further, theresultant set cement may be of higher quality because the type of andconcentration of additives was tailored to the original dry cement.

In some embodiments, device 306 may include an electromagnetic radiationsource 308 configured to emit or otherwise generate electromagneticradiation 310. Electromagnetic radiation source 308 may be any devicecapable of emitting or generating electromagnetic radiation, as definedherein. For example, electromagnetic radiation source 308 may be a lightbulb, a light emitting diode (LED), a laser, a blackbody, a photoniccrystal, an X-Ray source, combinations thereof, or the like. In someembodiments, a lens 312 collects or otherwise receives electromagneticradiation 310 and directs a beam 314 of electromagnetic radiation 310toward bulk material or powder 302. Lens 312 may be any type of opticaldevice configured to transmit or otherwise convey electromagneticradiation 310 as desired. For example, lens 312 may be a normal lens, aFresnel lens, a diffractive optical element, a holographic graphicalelement, a mirror (e.g., a focusing mirror), a type of collimator, orany other electromagnetic radiation-transmitting device known to thoseskilled in the art. Some embodiments omit lens 312 from device 306 andelectromagnetic radiation source 308 conveys electromagnetic radiation310 toward bulk material or powder 302 directly from the electromagneticradiation source 308. In some embodiments, lens 312 includes a pluralityof optical elements such as lenses and mirrors configured to directlight from electromagnetic radiation source 308 into bulk material orpowder 302.

In one or more embodiments, device 306 may also include a samplingwindow 316 arranged adjacent to or otherwise in contact with bulkmaterial or powder 302 for detection purposes. In some embodiments,sampling window 316 includes any one of a variety of transparent, rigidor semi-rigid materials that allow transmission of electromagneticradiation 310 therethrough. For example, sampling window 316 may includematerials such as, but not limited to, glasses, plastics,semi-conductors, crystalline materials, sapphire, polycrystallinematerials, hot or cold-pressed powders, combinations thereof, or thelike.

After passing through sampling window 316, electromagnetic radiation 310impinges upon and optically interacts with bulk material or powder 302,including any analytes present within bulk material or powder 302. As aresult, bulk material 302 generates and reflects optically interactedradiation 318. Those skilled in the art, however, will readily recognizethat alternative variations of device 306 allow optically interactedradiation 318 to be transmitted, scattered, diffracted, absorbed,emitted, or re-radiated by and/or from the bulk material or powder 302,or one or more analytes present within the bulk material or powder 302,without departing from the scope of the disclosure.

ICEs 320 a, 320 b and 320 c (hereinafter collectively referred to asICEs 320) may be included in device 306. ICE 320 a directs or otherwisereceives optically interacted radiation 318, generated by theinteraction with bulk material or powder 302. ICE devices 320 mayinclude spectral components substantially similar to ICE 100 describedabove with reference to FIG. 1. Accordingly, in operation ICE 320 areceives the optically interacted radiation 318 and produces modifiedelectromagnetic radiation 322 corresponding to a particularcharacteristic of interest of the bulk material or powder 302. Inparticular, the modified electromagnetic radiation 322 iselectromagnetic radiation that has optically interacted with ICE 320 aand obtains an approximate mimicking of the regression vectorcorresponding to the characteristic of interest. In some embodiments,the characteristic of interest corresponds to bulk material or powder302. In other embodiments, the characteristic of interest corresponds toa particular analyte found in the bulk material or powder 302. In someembodiments, the characteristic of interest may be air contained in aflow of bulk material or powder 302.

It should be noted that, while FIG. 3 depicts ICE 320 a as receivingoptically interacted radiation 318 from bulk material or powder 302, anICE component may be arranged at any point along the optical train ofthe device 306, without departing from the scope of the disclosure. Forexample, in one or more embodiments, ICE 320 b (as shown in dashedlines) may alternatively be arranged within the optical train prior tothe sampling window 316 and equally obtain substantially the sameresults. In other embodiments, sampling window 316 may serve a dualpurpose as both a transmission window and a substrate for one of ICEs320 (i.e., a spectral component). In yet other embodiments, the ICEcomponents 320 may generate modified electromagnetic radiation 322through reflection, instead of transmission therethrough.

Moreover, while only one ICE 320 a is shown in device 306, embodimentsare contemplated herein which include the use of at least two ICEs 320in device 306 configured to cooperatively determine the characteristicof interest in bulk material or powder 302. For example, two or more ICE320 arranged in series or parallel within device 306 receive opticallyinteracted radiation 318 thereby enhancing sensitivities and detectorlimits of device 306. In some embodiments, two or more ICEs 320 may bearranged on a movable assembly, such as a rotating disc or anoscillating linear array, which moves such that individual ICEs 320 areable to be exposed to or otherwise optically interact withelectromagnetic radiation 310 for a distinct brief period. The two ormore ICEs 320 in any of these embodiments may be associated ordisassociated with the characteristic of interest in bulk material orpowder 302. In other embodiments, the two or more ICEs 320 have apositive or a negative correlation with the characteristic of interest.Further, according to some embodiments, the two or more ICEs 320 mayhave opposite correlation with the characteristic of interest. In suchembodiments, while a signal in detector 324 increases with an increasein the characteristic of interest for a first ICE 320, the signal indetector 324 decreases for a second ICE 320.

In some embodiments, it may be desirable to monitor more than onecharacteristic of interest at a time using device 306. In suchembodiments, various configurations for multiple ICEs 320 can be used,where each ICE 320 is configured to detect a particular and/or distinctcharacteristic of interest corresponding, for example, to bulk materialor powder 302 or to an analyte in the bulk material or powder 302. Someembodiments analyze the characteristic of interest sequentially usingmultiple ICEs 320 interacting with a single beam of optically interactedradiation 318 reflected from or transmitted through bulk material orpowder 302. For example, some embodiments include multiple ICEs 320arranged on a rotating disc. In such embodiments, the beam of opticallyinteracted radiation 318 interacts with individual ICEs 320 for areduced time. Advantages of this approach can include the ability toanalyze multiple characteristics of interest within bulk material orpowder 302 using device 306 and the opportunity to assay additionalcharacteristics simply by adding additional ICEs 320 to the rotatingdisc corresponding to those additional characteristics.

Other embodiments place multiple devices 306 at a single location alongcontainer 304, where each device 306 contains a unique ICE 320 that isconfigured to detect a particular characteristic of interest. In suchembodiments, a beam splitter can divert a portion of the opticallyinteracted radiation 318 reflected by, emitted from, or transmittedthrough the bulk material or powder 302 and into each one of devices306. Each one of devices 306, in turn, can be coupled to a correspondingdetector (e.g., detector 324) or detector array that is configured todetect and analyze an output of electromagnetic radiation from therespective optical computing device. Parallel configurations of opticalcomputing devices can be particularly beneficial for applications thatrequire low power inputs and/or no moving parts.

Those skilled in the art will appreciate that any of the foregoingconfigurations can include a series configuration in any of the presentembodiments. For example, a movable housing may arrange two devices 306in series to perform an analysis at a single location in container 304.Likewise, multiple detection stations, each containing devices 306 inparallel, can perform a similar analysis in series.

Modified electromagnetic radiation 322 generated by ICE 320 a maysubsequently be conveyed to the detector 324 for quantification of thesignal. Detector 324 may be any device capable of detectingelectromagnetic radiation, such as an optical transducer. In someembodiments detector 324 is a thermal detector such as a thermopile orphoto-acoustic detector, a semiconductor detector, a piezo-electricdetector, a charge coupled device (CCD) detector, a video or arraydetector, a split detector, a photon detector (such as a photomultipliertube), photodiodes, combinations thereof, or the like, or otherdetectors known to those skilled in the art.

In some embodiments, detector 324 may be configured to produce an outputsignal 326 in real-time or near real-time in the form of a voltage (orcurrent) that corresponds to the particular characteristic of interestin bulk material or powder 302. The voltage returned by detector 324 isessentially the dot product of the optical interaction of opticallyinteracted radiation 318 with ICE 320 a as a function of theconcentration of the characteristic of interest. As such, output signal326 produced by detector 324 and the characteristic of interest arerelated to one another. For example, output signal 326 may be directlyproportional to the characteristic of interest. In other embodiments,however, the relationship may correspond to a polynomial function, anexponential function, a logarithmic function, and/or a combinationthereof. In some embodiments, output signal 326 associated with ICE 320a may be negatively correlated with the characteristic of interest.Accordingly, output signal 326 decreases when the characteristic ofinterest increases.

In some embodiments, device 306 may include a second detector 328, whichmay be similar to first detector 324 in that it may be any devicecapable of detecting electromagnetic radiation. Similar to seconddetector 216 of FIG. 2, second detector 328 of FIG. 3 detects radiatingdeviations stemming from the electromagnetic radiation source 308.Accordingly, a beam splitter 311 (in dashes) may direct a portion ofelectromagnetic radiation 310 to detector 328, which may be configuredto monitor radiating deviations in electromagnetic radiation source 308.In some embodiments, another ICE device 320 c (shown in dashes) beforedetector 328 modifies the electromagnetic radiation impinging ondetector 328. Undesirable radiating deviations can occur in theintensity of the electromagnetic radiation 310 due to a wide variety ofreasons and potentially causing various negative effects on the outputof the device 306. These negative effects can be particularlydetrimental for measurements taken over a period. In some embodiments,radiating deviations can occur due to a build-up of a layer of residualmaterial on sampling window 316. This reduces the amount and quality oflight ultimately reaching first detector 324. Without propercompensation, such radiating deviations could result in false readingsand output signal 326 may inaccurately relate the characteristic ofinterest.

To compensate for these undesirable effects, second detector 328generates a compensating signal 330 generally indicative of theradiating deviations of the electromagnetic radiation source 308,thereby normalizing output signal 326 generated by first detector 324.As illustrated, second detector 328 may receive a portion of opticallyinteracted radiation 318 via a beam splitter 332 in order to detect theradiating deviations. In some embodiments, second detector 328 receiveselectromagnetic radiation from any portion of the optical train indevice 306 to detect radiating deviations, without departing from thescope of the disclosure.

In some applications, output signal 326 and compensating signal 330 maybe conveyed to or otherwise received by a signal processor 334communicably coupled to both detectors 324, 328. Signal processor 334may be a computer including a non-transitory machine-readable medium,configured to normalize output signal 326 using compensating signal 330,in view of any radiating deviations detected by second detector 328. Insome embodiments, computing output and compensating signals 326, 330 mayentail computing a ratio of the two signals 326, 330. For example, theconcentration or magnitude of each characteristic of interest determinedusing optical computing device 306 can be fed into an algorithm run bysignal processor 334. The algorithm may be configured to makepredictions on how the bulk material or powder 302 in combination withcement slurry additives, optionally at varying concentrations, willbehave in a cement slurry.

Systems similar to that illustrated in FIG. 3 may be useful in analyzingbulk material or powders. For example, a system may include a probe thatcan be inserted into a dry cement for analysis of a characteristicthereof. As such, the dry cement may be contained within a container nothaving a device 306 connected thereto (e.g., a bag of dry cement asshipped from a distributor). Further, the dry cement may be a pile ormound of dry cement in open air.

Those skilled in the art will readily recognize that, in one or moreembodiments, electromagnetic radiation derives from the bulk material orpowder 302 itself. For example, various substances naturally radiateelectromagnetic radiation that is able to interact with at least one ofICE components 320. In some embodiments, for example, bulk material orpowder 302 or a substance within the bulk material or powder 302 may bea blackbody radiating substance configured to radiate heat that mayoptically interact with at least one of ICE components 320. In otherembodiments, the bulk material or powder 302 or the substance within thebulk material or powder 302 may be radioactive or chemo-luminescent andemit electromagnetic radiation that is able to interact with ICE 320. Inyet other embodiments, mechanical, magnetic, electric, actuation induceselectromagnetic radiation from bulk material or powder 302 or from asubstance within the bulk material or powder 302. For instance, in atleast one embodiment, a voltage across bulk material or powder 302 orthe substance within bulk material or powder 302 induces theelectromagnetic radiation. As a result, in embodiments contemplatedherein the electromagnetic radiation source 308 may be omitted from theparticular optical computing device.

FIG. 4 illustrates an exemplary housing 400 that may be used to house anoptical computing device, according to one or more embodiments. In someembodiments, housing 400 may be mechanically coupled to container 304using, for example, mechanical fasteners, brazing or welding techniques,adhesives, magnets, combinations thereof or the like. Housing 400substantially protects the internal components of device 306 from damageor contamination from the external environment. Those skilled in theart, however, will readily recognize that several alternative designsand configurations of housings used to house the optical computingdevices are suitable for the presently disclosed systems and methods.Indeed, housing embodiments described and disclosed herein are by way ofexample only, and should not limit the scope to the exemplary systemsand methods disclosed herein.

As illustrated, the housing 400 may be in the general form of a bolt450, which encloses the various components of an optical computingdevice, such as device 306 of FIG. 3. In one embodiment, components ofthe device 306 housed within housing 400 may be generally housed withina stem 452 of a bolt 450, and bolt 450 may have a hex head 454 formanual manipulation of housing 400 using, for example, a wrench or othersuitable torque-generating hand tool.

In at least one embodiment, housing 400 defines external threads 456that are compatible with corresponding mating pipe threads provided in,for example, an opening defined in container 304 (FIG. 3) that isconfigured to receive housing 400. A thread sealant between threads 456and the mating pipe threads may prevent leakage of moisture or anyundesirable substance through the juncture between housing 400 and thepipe. Sampling window 316 is configured to be in optical communicationwith bulk material or powder 302 (FIG. 3) and allows optical interactionbetween bulk material or powder 302 and other internal components ofinternally housed device 306.

FIG. 5 illustrates a system 500 for storing and conveying raw materialsfrom storage containers 505 to transport units 550 including an opticalcomputing device 506, according to some embodiments. System 500 includesa storage container 505 including at least one of a hopper 502 or astorage bin 504 to store a bulk material or powder 501. Hopper 502 maybe a storage container with an open top, while storage bin 504 mayinclude a top enclosure (e.g., a tank). Bulk material or powder 501 mayinclude any one of fly ash, silica flour, salts, or any of the materialsmentioned above in a dry cement combination, including cement additivesin powder form. Other dry materials 501 besides dry cement that may betransferred in hopper 502 include salt, lime, sand, POZMIX®, and thelike. In some embodiments of system 500, hopper 502 conveys differentmaterials through transfer tube 507 a into scale tank 510, sequentially.Transfer tube 507 a conveys bulk material or powder 501 from any one ofstorage containers 505 (including storage bin 504) to a scale tank 510.In some embodiments, a pump 530 creates a negative air pressure in thescale tank to generate a flow of bulk material or powder 501, thus‘pulling’ bulk material or powder 501 through transfer tube 507 a. Inother embodiments, the bulk material may gravity flow from 505 through507 a into 510. Scale tank 510 receives raw materials from differentstorage containers 505 such as hopper 502 and storage bin 504 and formsa mix, such as dry cement. The mixture may be developed by ribbonblending, jets, multiple transfers and such, with optical computingdevice 506 d determining when the mixture is satisfactorily homogeneous.Transfer tube 507 b conveys the mixed materials to a truck 550 a or aship 550 b for shipping the blended materials (e.g., dry cement) to adeployment location. Transfer tubes 507 a and 507 b will be referredhereinafter to as transfer tubes 507. In some embodiments transfer tube507 b includes a flow of the bulk material or powder mixed with air, theair provided by an air pump 540 creating a positive air pressure in thescale tank, thus ‘pushing’ bulk material or powder 501 through transfertube 507 b. In some embodiments, the role of pump 530 and air compressor540 may be reversed, so that an air compressor 540 ‘pushes’ raw materialfrom storage containers 505 into scale tank 510. Or in some embodimentspump 530 may be used to ‘pull’ a material mix from scale tank 510 totransport units 550 a (e.g., a truck) and 550 b (e.g., a ship).Transport units 550 a and 550 b will be referred hereinafter to astransport units 550.

In some embodiments, it may be desirable to know in real time that thecorrect material is in any one of storage containers 505, or in any oneof transfer tubes 507, scale tank 510, or even within transport units550. Accordingly, system 500 includes a plurality of optical computingdevices disposed in different locations. Optical computing device 506 ais located within hopper 502. Optical computing device 506 b is locatedwithin storage bin 504. Optical computing device 506 c is located withintransfer tube 507 a. Optical computing device 506 d is located withinscale tank 510. Optical computing device 506 e is located withintransfer tube 507 b. Optical computing device 506 f is located withintruck 550 a, and optical computing device 506 g is located within ship550 b. Optical computing devices 506 a-g will be collectively referredto hereinafter as optical computing devices 506. In some embodiments, atleast one of optical computing devices 506 may be as optical computingdevice 306 in FIG. 3.

System 500 also includes a signal processor 534 having a processorcircuit 536 and a memory circuit 537 storing commands. Signal processor534 may be similar to signal processor 334 of FIG. 3. When executed byprocessor circuit 536 the commands cause signal processor 534 to performa method including receiving a first signal from a first opticalcomputing device 506 a at a first location in system 500. The commandsmay also cause signal processor 534 to perform the step of receiving asecond signal from a second optical computing device 506 b at a secondlocation in system 500. The first and second location in system 500 maybe any one of storage containers 505, transfer tubes 507, scale tank510, or even transport units 550. In that regard, optical computingdevices 506 and signal processor 534 may exchange data and signals via awire connection, or a wireless connection. The first and second signalmay result from a light interacted with a bulk material or powder 501,and at least one of the first and second signals results from anelectromagnetic radiation modified by an ICE. In some embodiments, thecommands further cause signal processor 534 to perform the step ofdetermining from the first and second signal a characteristic of thebulk material or powder, or of the flow of the bulk material or powder.More generally, processor circuit 536 may execute commands stored inmemory circuit 537 that cause signal processor 534 to perform at leastone of the steps in any method consistent with the present disclosure. AHuman Machine Interface (HMI) 560 may be coupled to signal processor534, and be configured to monitor the operation of system 500 by a humanoperator. Accordingly, HMI 560 may issue warnings, alert messages, oralarms, based on the data provided by signal processor 534 uponcollecting signals from each of optical computing devices 506.

Optical computing devices 506 enable real time monitoring and detectionof various compounds in most any phase, including powders, liquids andslurries. For example, an ICE in any one of optical computing devices506 (e.g., ICE 100 in FIG. 1) may identify cement powder ingredientsused in dry cement compositions. Monitoring and detecting the chemicalcomposition (or at least key ingredients) through optical computingdevices 506 enables identification and verification of bulk material orpowder 501 in hopper 502, in storage bin 504 or in one of the transfertubes 507 a and 507 b. Optical computing devices 506 also enabledetection of the condition of bulk material or powder 501. For example,optical computing devices 506 may determine when excessive moisture ordecomposition occurs in storage or while conveyed in and out of scaletank 510. A window or a probe provides optical communication betweenoptical computing devices 506 and storage containers 505, transfer tubes507, or transport units 550. The window may be similar to window 316 ofFIG. 3, and the probe may include a waveguide device to transmitelectromagnetic radiation, such as an optical fiber.

Accordingly, methods and systems consistent with the present disclosureprovide fast identification of dry materials contained in a storage bin,a hopper, or a pneumatic conveyor. System 500 also includes a programmedcontrol system with alarms and reporting to prevent contamination ofbulk materials or powders from interconnecting piping with differentstorage bins, or from different materials delivered to the storage binor hopper. Accordingly, system 500 enhances the confidence level foradding to a blend the correct materials in their suitable condition.Accordingly, embodiments consistent with the present disclosure decreasethe likelihood of ruined bulk material or powder batches being disposedof. Thus decreasing waste disposal costs and material costs to theplant. Methods and systems consistent with the present disclosure alsodecrease the likelihood of compromised bulk material blends: arriving onlocation, mixing in a blend, and pumped into a borehole. This alsodecreases the cost of poor quality, and the likelihood of downtime dueto test and repair of damaged structures. Furthermore, embodimentsconsistent with the present disclosure decrease occurrence of equipmentdamage due to flash setting in the mixing and pumping system and/or poorslurry mixability.

FIG. 6 illustrates a conveyor 600 in a pneumatic conveying system usingoptical flow characterization data obtained with optical computingdevices 506 h, 506 i, and 506 j, according to some embodiments.Consistent with embodiments disclosed herein, conveyor 600 may belocated upstream or downstream of a scale tank (e.g., scale tank 510 ofFIG. 5) to form a blend with different bulk materials or powders.Optical computing devices 506 h-j measure chemical compositions inflowing bulk materials or powders 501 under rapid flow conditions in apneumatic tube such as transfer tube 507. More generally, embodiments ofthe present disclosure may include a transfer tube 507 that is part ofother type of conveyor system, such as a screw conveyor (with a helicoidblade rotating along the axis of transfer tube 507), or a gravity-basedconveying system, where transfer tube 507 makes an angle with thehorizontal to facilitate displacement of bulk material or powder 501 bygravity. Accordingly, optical computing device 506 makes measurements atthe speed it takes to collect an electromagnetic signal in an opticaldetector (e.g., detectors 324 and 328, cf. FIG. 3). As such, rapidlyflowing fluids and powders can be measured using optical computingdevice 506 because bulk material and powder 501 moves slowly relative tothe measurement speed of optical computing device 506. In someembodiments, optical computing devices 506 h-j measure moisture contentof materials in a high velocity pneumatic transfer drying system.Optical computing devices 506 h-j may also be used in other materialconveying systems with a reduced rate of material transfer, as known inthe art. In that regard, real time measurement of the moisture contentof the air in the pneumatic transfer tube 507 flow would be valuable todetect potentially negative conditions associated with high moisturelevels or high relative humidity.

The optical computing devices 506 h-j may each be communicably coupledto a signal processor 634 configured to process data obtained by eachoptical computing devices 506 h-j. Some embodiments include opticalcomputing devices 506 mounted on a wall of transfer tube 507, or insidethe transfer tube in a rod, tube, pipe, or other structure exposed tothe flow of bulk material or powder 501. In some embodiments, opticalcomputing devices 506 may be located along a direction substantiallyperpendicular to the direction of flow of the bulk material or powder intransfer tube 506. Optical computing device 506 is able to detectdifferent flow types 601, 602, and 603 of bulk material or powder 501flowing through transfer tube 507 and in what portion of transfer tube507. For example, flow type 601 includes material flow aerated at thetop of transfer tube 507, flow type 602 may include more dense materialflow in the middle portion of transfer tube 507, and flow type 603 mayinclude an even more dense material flow at the bottom portion oftransfer tube 507.

In some embodiments, flow types 601, 602, and 603 relate to asegregation of the material flow according to a particle size, with flowtype 601 at the top mostly including fines (reduced size particles), andflow type 603 at the bottom containing coarser particles of the sameneat or blended material. Accordingly, embodiments of the presentdisclosure enable determining a flow profile in conveyor 600 and, moreparticularly, within transfer tube 507. Flow types 601, 602, and 603 maybe apparent when the transfer tube 507 is horizontally positioned.However, there is no limitation to the specific orientation of transfertube 507 with respect to gravity. More generally, conveyor 600 may beoriented at any angle relative to horizontal or gravity, includingvertically oriented or any angular configuration between horizontal andvertical.

Moreover, while FIG. 6 illustrates a straight transfer tube 507, thereis no limitation as to the specific shape of transfer tube 507 inconveyor 600. In some embodiments, for instance, conveyor 600 mayinclude an elbow portion having a curve or even a sharp angle (e.g., a90° angle). There is also no limitation as to the number of flow typesthat may be present inside conveyor 600. For example, some embodimentsmay include multiple flow types (e.g., two-phase, dense phase, or dilutephase flow), or a homogenously aerated flow throughout (e.g., dilutephase flow).

In some embodiments, data obtained with characterization of the flowthrough transfer tube 507 by optical measurement systems 400 enablesimproving performance of the transfer system. Accordingly, using datafrom optical measurement systems 400, the conveying airflow rate (e.g.,through pump 530 of FIG. 5) may be adjusted to provide a homogeneousflow moving at a desired speed. Some embodiments use data from opticalmeasurement systems 400 to adjust conveying air pressure (e.g., throughcompressor 540, cf. FIG. 5), and piping layout (e.g., length, diameter,orientation, and trajectory of transfer tubes 506). In some embodiments,a flow profile provided by optical measurement systems 400 may indicatewhen blended materials (e.g., downstream from scale tank 510, cf. FIG.5) are segregating during the pneumatic transfer. Furthermore, somepowders may have a tendency to adhere to the inside surface of transfertube 507, forming a layer or a plaque of residual material that mayeventually corrode or damage transfer tube 507. The residual materialeventually reduces material flow rate, or some constituents may be lostto the blend, thus affecting the blend's performance and/orcontaminating following, possibly different blends. Accordingly, opticalmeasurement systems 400 may determine material deposition in portions ofthe interior surface of transfer tube 507, and even determine thickness,shape, and size of the layer of residual material. Accordingly,adjusting airflow rate and pressure in real time produces a desiredconveying rate with reduced material segregation and maintained blendquality.

Some embodiments include at least two optical computing devices 506arranged at selected positions along a direction of flow of the bulkmaterial or powder in transfer tube 507. A time correlation ofmeasurements between two or more optical computing devices 506 alongtransfer tube 507 enables measurement of flow velocities of bulkmaterial or powder 501. For example, in a “slug” flow type, relativelyrarefied portions of flow follow dense portions of material (“slugs”).In such conditions, optical computing device 506 may detect the passageof the slug by a change in the density of the material flow.Accordingly, a first optical computing device 506 may record the passageof a slug at a first time and a first position. Thus, and a secondoptical computing device records the passage of the slug at a secondtime and a second position; thus, signal processor 634 may determine thevelocity or flow rate of the slug by correlating the measurements ofoptical computing devices 506 h and 506 j. In embodiments where littlematerial is transferred the first and second optical computing devices506 record the passage of discrete portions of material forming a firstand a second string of high and low density measurements. Signalprocessor 634 obtains the speed of material flow by correlating thefirst and second strings of measurements in time, with knowledge of thedistance separating the first and second optical computing devices 506.

FIG. 7 illustrates a flowchart including steps in a method 700 foroperating a pneumatic conveying system using optical flowcharacterization data, according to some embodiments. Embodimentsconsistent with method 700 include operating a pneumatic conveyor in asystem for storing and conveying materials from containers to transportunits (e.g., conveyor 600, cf. FIG. 6, and system 500, cf. FIG. 5). Apneumatic conveyor as used in some embodiments of method 700 may includea transfer tube as any one of transfer tubes 507 in FIG. 5. Accordingly,a pneumatic conveyor in methods consistent with method 700 may includeat least one optical computing device that has an ICE, a detector, and asignal processor (e.g., detectors 324 and 328, and signal processor 334,cf. FIG. 3, and optical computing device 506, cf. FIG. 4). In someembodiments the optical computing device is mounted on a transfer tubeto detect a flow type of a bulk material or powder (e.g., opticalcomputing device 506, transfer tube 507, bulk material or powder 501,and flow types 601, 602, 603, cf. FIG. 6). In some instances, at leastone of the steps in method 700 includes using computers and optionallyartificial neural networks. For example, in some embodiments at leastone or more of the steps in method 700 is performed by a signalprocessing circuit including a memory circuit storing commands executedby a processor circuit (e.g., signal processor 534, processing circuit536, and memory circuit 537, cf. FIG. 5). Steps in methods consistentwith the present disclosure may include at least any of the steps inmethod 700, performed in any order. Furthermore, embodiments consistentwith the present disclosure may include one or more of the steps inmethod 700 performed overlapping in time, or simultaneous in time.

Step 710 includes optically interacting a flow of bulk material orpowder in a pneumatic conveyor with an ICE. In some embodiments, step710 includes providing an electromagnetic radiation source, and in someembodiments step 710 may include using an electromagnetic radiationgenerated internally in the pneumatic conveyor (e.g., by a flare sparkedinside a transfer tube). Further, in some embodiments step 710 includesusing a natural electromagnetic radiation from the sun or any othernatural source of electromagnetic radiation. Step 720 includes detectingthe modified electromagnetic radiation resulting from opticallyinteracting the flow of bulk material or powder with the ICE, in thedetector. In some embodiments, step 720 includes processing a detectorsignal with the signal processor. Accordingly, processing a detectorsignal may include finding a time correlation between signals providedby at least two optical measurement systems disposed at selectedlocations.

Step 730 includes producing an output signal correlated with thecharacteristic of the flow of bulk material or powder. In someembodiments, step 730 includes determining the characteristic of theflowing bulk material or powder. The characteristic of the bulk materialor powder may be an identification of the bulk material or powder, apurity value (e.g., 98%, 99% concentration or higher), a contaminantconcentration value, a moisture concentration value, a particle sizevalue, a homogeneity, an air content, and a flow speed, among others. Insome embodiments, determining a particle size is useful in determining aquality of the bulk material or powder stored in the container withinthe system for storing and conveying raw materials. For example, largerparticle sizes that can lead to a reduced strength set cement maybenefit from a strengthening cement slurry additive (e.g., fibers orother resilient particles). In the other hand, bulk materials or powderswith a smaller particle size typically use more water to hydratecompletely because of the increased surface area relative to weight.

Step 740 includes modifying flow parameters to maintain the quality of ablend according to the characteristic of the flow of bulk material orpowder. In some embodiments, step 740 includes adjusting flow parametersto improve or maintain the quality of a blend according to the value ofthe characteristic of the flowing bulk material or powder. For example,step 740 may include storing the collected data and correlating the datawith a success or failure measure. In some embodiments step 740 includescorrelating a measurement from the at least one optical computing devicewith a determination that a cement mix was satisfactory, or not. Step740 may also include reducing blend segregation and degradation, thusincreasing blend homogeneity and maintaining blend quality.

Step 750 includes modifying flow parameters to reduce maintenance andequipment cost according to the characteristic of the flow of bulkmaterial or powder. Further, in some embodiments step 750 includesproviding data for material conveying tests, and incorporating the datain models including economic factors. Some of the economic factors mayinclude the cost of equipment in the conveying system (e.g., pumps, aircompressors, pipes of given length and diameter), and the structures inwhich the system will be deployed (i.e., pipeline layout). Accordingly,step 750 may include optimizing the piping layout design in the materialconveying system, thus reducing installation costs due to a reducednumber of components such as pipes, pumps and compressors. Step 750 mayinclude reducing piping material cost due to a reduced number ofcomponents, and reducing maintenance cost from a better and moredetailed knowledge of component erosion (e.g., on the inside face of thetransfer tubes) provided by step 730.

Step 750 may include optimizing, with the data provided in step 730, theconveying airflow through the system, and reducing equipment cost due tosmaller size equipment being purchased. In some embodiments, step 750includes reducing energy consumption, cost, and environmental impact ofthe material conveying system throughout the life of the system. Andreducing the amount of time to complete a batch and deliver a materialblend to the well site on or ahead of time. This reduces for example thenumber of failed cement jobs, which can save costs in terms of liabilityand repair.

When the system detects a discrepancy in the material contained in thetransfer tube versus the criteria stored in the system, some embodimentsshut down the transfer process in the transfer system. For example, avalve in a transfer tube between a storage container and the scale tankmay be closed. Or a valve in a transfer tube between the scale tank anda transportation unit may be closed. Some embodiments issue a warning(pop-up) on the screen of the HMI, stating what the discrepancy is, andthat the operator may address before allowing continued operation of thematerial transfer from the storage container to the scale tank. In someembodiments, the HMI is configured to record the alert event and theoperator's response to the warning in the system for later reporting.

It is recognized that the various embodiments herein directed tocomputer control and artificial neural networks, including variousblocks, modules, elements, components, methods, and algorithms, can beimplemented using computer hardware, software, combinations thereof, andthe like. To illustrate this interchangeability of hardware andsoftware, various illustrative blocks, modules, elements, components,methods and algorithms have been described generally in terms of theirfunctionality. Whether such functionality is implemented as hardware orsoftware will depend upon the particular application and any imposeddesign constraints. For at least this reason, it is to be recognizedthat one of ordinary skill in the art can implement the describedfunctionality in a variety of ways for a particular application.Further, various components and blocks can be arranged in a differentorder or partitioned differently, for example, without departing fromthe scope of the embodiments expressly described.

Computer hardware used to implement the various illustrative blocks,modules, elements, components, methods, and algorithms described hereincan include a processor configured to execute one or more sequences ofinstructions, programming stances, or code stored on a non-transitory,computer-readable medium. The processor can be, for example, a generalpurpose microprocessor, a microcontroller, a digital signal processor,an application specific integrated circuit, a field programmable gatearray, a programmable logic device, a controller, a state machine, agated logic, discrete hardware components, an artificial neural network,or any like suitable entity that can perform calculations or othermanipulations of data. In some embodiments, computer hardware canfurther include elements such as, for example, a memory (e.g., randomaccess memory (RAM), flash memory, read only memory (ROM), programmableread only memory (PROM), erasable read only memory (EPROM)), registers,hard disks, removable disks, CD-ROMs, DVDs, or any other like suitablestorage device or medium.

Executable sequences described herein can be implemented with one ormore sequences of code contained in a memory. In some embodiments, suchcode can be read into the memory from another machine-readable medium.Execution of the sequences of instructions contained in the memory cancause a processor to perform the process steps described herein. One ormore processors in a multi-processing arrangement can also be employedto execute instruction sequences in the memory. In addition, hard-wiredcircuitry can be used in place of or in combination with softwareinstructions to implement various embodiments described herein. Thus,the present embodiments are not limited to any specific combination ofhardware and/or software.

As used herein, a machine-readable medium will refer to any medium thatdirectly or indirectly provides instructions to a processor forexecution. A machine-readable medium can take on many forms including,for example, non-volatile media, volatile media, and transmission media.Non-volatile media can include, for example, optical and magnetic disks.Volatile media can include, for example, dynamic memory. Transmissionmedia can include, for example, coaxial cables, wire, fiber optics, andwires that form a bus. Common forms of machine-readable media caninclude, for example, floppy disks, flexible disks, hard disks, magnetictapes, other like magnetic media, CD-ROMs, DVDs, other like opticalmedia, punch cards, paper tapes and like physical media with patternedholes, RAM, ROM, PROM, EPROM, and flash EPROM.

Embodiments disclosed herein include:

A. A method that includes optically interacting a flow of bulk materialor powder in a pneumatic conveyor with an integrated computationalelement (“ICE”) configured to modify an electromagnetic radiationaccording to a characteristic of the flow of bulk material or powder,detecting the modified electromagnetic radiation with a detector,producing an output signal with a signal processor, the output signalbeing correlated to the characteristic of the flow of bulk material orpowder, and modifying at least one of a feed rate or a differential airpressure in the pneumatic conveyor in response to the characteristic ofthe flow of bulk material or powder, wherein the bulk material or powdercomprises at least one of a dry cement or a dry cement component.

B. A device that includes a processor circuit, and a memory circuitstoring commands, which, when executed by the processor circuit, causesthe device to perform a method comprising receiving a first signal froma first optical computing device at a first location in a system forstoring and conveying materials, receiving a second signal from a secondoptical computing device at a second location in the system for storingand conveying materials, wherein the first and second signal result froma light interacted with a bulk material or a powder flowing in atransfer tube, and at least one of the first and second signals resultsfrom modifying the interacted light with an Integrated ComputationalElement (ICE) according to a characteristic of the flow of bulk materialor powder, and determining, from the first and second signal, thecharacteristic of the flow of bulk material or powder along the transfertube.

C. A method that includes receiving an output signal from each of aplurality of optical computing devices disposed in separate locations ina pneumatic conveyor flowing a bulk material or powder, processing eachof the output signals from the plurality of optical computing deviceswith a signal processor, determining a characteristic of the flow ofbulk material or powder based on processing of the output signals, andmodifying a physical parameter of the pneumatic conveyor in response tothe value of the characteristic of the flow of bulk material or powder.

Each of embodiments A, B, and C may have one or more of the followingadditional elements in any combination: Element 1: wherein thecharacteristic of the flow of bulk material or powder is a concentrationof air in the bulk material or powder, and wherein modifying at leastone of a feed rate or a differential air pressure comprises increasingan air pressure when the concentration of air in the bulk material orpowder is below a threshold value. Element 2: wherein the characteristicof the flow of bulk material or powder is a moisture content of the bulkmaterial or powder and further comprising reducing the moisture contentof the bulk material or powder when the moisture content is greater thana threshold value. Element 3: wherein the characteristic of the flow ofbulk material or powder is a layer of residual material on an inner wallof the pneumatic conveyor, and modifying at least one of a material feedrate or a differential air pressure comprises increasing the flowvelocity when the layer of residual material is detected on the innerwall of the pneumatic conveyor. Element 4: wherein the characteristic ofthe flow of bulk material or powder is a blend composition of at leasttwo bulk materials or powders, the method further comprising adjustingan amount of one of the at least two bulk materials or powders accordingto a desired blend composition. Element 5: further comprisingdetermining whether the flow of the bulk material or powder is adense-phase, multi-phase flow or a dilute phase flow based on thecharacteristic of the bulk material or powder. Element 6: wherein thecharacteristic of the flow of bulk material or powder is a particle sizeof the bulk material or powder flowing in the pneumatic conveyor.

Element 7: wherein the first location is within a pneumatic conveyor inthe system for storing and conveying materials. Element 8: wherein thesecond location is within a pneumatic conveyor located downstream fromthe first location in the system for storing and conveying materials.Element 9: wherein the first location and the second location areaxially offset from each other along a pneumatic conveyor in the systemfor storing and conveying materials. Element 10: wherein the firstlocation and the second location are offset along a directionsubstantially perpendicular to a direction of flow of a bulk material orpowder in a pneumatic conveyor of the system for storing and conveyingmaterials.

Element 11: wherein at least two of the plurality of optical computingdevices are disposed in different locations along the direction of theflow of bulk material or powder, the method further comprisingcorrelating in time the output signals from the at least two of theplurality of optical computing devices in the signal processor, anddetermining a flow rate of the bulk material or powder. Element 12:wherein determining a characteristic of the flow of bulk material orpowder comprises determining a flow profile in the pneumatic conveyor.Element 13: wherein determining a characteristic of the flow of bulkmaterial or powder comprises determining whether a flow of the bulkmaterial or powder is a segregated flow or a homogenous flow. Element14: wherein modifying a characteristic of the pneumatic conveyorcomprises modifying at least one of a material feed rate or adifferential air pressure in the pneumatic conveyor. Element 15: whereinmodifying a characteristic of the pneumatic conveyor comprises modifyingat least one of a pipe length, a pipe diameter, or a pipe trajectory inthe pneumatic conveyor. Element 16: wherein determining a characteristicof the bulk material or powder comprises determining at least partiallya shape and a size of a layer of residual material deposited inside thepneumatic conveyor. Element 17: further comprising determining adifference in the characteristic of the flow of bulk material or powderat the different locations in the pneumatic conveyor.

The exemplary embodiments described herein are well adapted to attainthe ends and advantages mentioned as well as those that are inherenttherein. The particular embodiments disclosed above are illustrativeonly, as the exemplary embodiments described herein may be modified andpracticed in different but equivalent manners apparent to those skilledin the art having the benefit of the teachings herein. Furthermore, nolimitations are intended to the details of construction or design hereinshown, other than as described in the claims below. It is thereforeevident that the particular illustrative embodiments disclosed above maybe altered, combined, or modified and all such variations are consideredwithin the scope and spirit of the present invention. The inventionillustratively disclosed herein suitably may be practiced in the absenceof any element that is not specifically disclosed herein and/or anyoptional element disclosed herein. While compositions and methods aredescribed in terms of “comprising,” “containing,” or “including” variouscomponents or steps, the compositions and methods can also “consistessentially of” or “consist of” the various components and steps. Allnumbers and ranges disclosed above may vary by some amount. Whenever anumerical range with a lower limit and an upper limit is disclosed, anynumber and any included range falling within the range is specificallydisclosed. In particular, every range of values (of the form, “fromabout a to about b,” or, equivalently, “from approximately a to b,” or,equivalently, “from approximately a-b”) disclosed herein is to beunderstood to set forth every number and range encompassed within thebroader range of values. Also, the terms in the claims have their plain,ordinary meaning unless otherwise explicitly and clearly defined by thepatentee. Moreover, the indefinite articles “a” or “an,” as used in theclaims, are defined herein to mean one or more than one of the elementthat it introduces. If there is any conflict in the usages of a word orterm in this specification and one or more patent or other documentsthat may be incorporated herein by reference, the definitions that areconsistent with this specification should be adopted.

As used herein, the phrase “at least one of” preceding a series ofitems, with the terms “and” or “or” to separate any of the items,modifies the list as a whole, rather than each member of the list (i.e.,each item). The phrase “at least one of” does not require selection ofat least one item; rather, the phrase allows a meaning that includes atleast one of any one of the items, and/or at least one of anycombination of the items, and/or at least one of each of the items. Byway of example, the phrases “at least one of A, B, and C” or “at leastone of A, B, or C” each refer to only A, only B, or only C; anycombination of A, B, and C; and/or at least one of each of A, B, and C.

The invention claimed is:
 1. A method comprising: optically interactinga flow of bulk material or powder in a pneumatic conveyor with anintegrated computational element (“ICE”) configured to modify anelectromagnetic radiation according to a characteristic of the flow ofbulk material or powder, the characteristic being selected from thegroup consisting of: a concentration of air in the bulk material orpowder, a layer of residual material on an inner wall of the pneumaticconveyor, a blend composition of at least two bulk materials or powders,a dense-phase flow state, a multi-phase flow state, a dilute phase flowstate, segregated flow state, and a homogeneous flow state; detectingthe modified electromagnetic radiation with a detector; producing anoutput signal with a signal processor, the output signal beingcorrelated to the characteristic of the flow of bulk material or powder;and modifying at least one of a feed rate or a differential air pressurein the pneumatic conveyor in response to the characteristic of the flowof bulk material or powder, wherein the bulk material or powdercomprises at least one of a dry cement or a dry cement component.
 2. Themethod of claim 1, wherein the characteristic of the flow of bulkmaterial or powder is the concentration of the air in the bulk materialor powder, and wherein modifying at least one of a feed rate or adifferential air pressure comprises increasing an air pressure when theconcentration of air in the bulk material or powder is below a thresholdvalue.
 3. The method of claim 1, wherein the characteristic of the flowof bulk material or powder is the layer of residual material on theinner wall of the pneumatic conveyor, and modifying at least one of amaterial feed rate or a differential air pressure comprises increasingthe flow velocity when the layer of residual material is detected on theinner wall of the pneumatic conveyor.
 4. The method of claim 1, whereinthe characteristic of the flow of bulk material or powder is the blendcomposition of the at least two bulk materials or powders, the methodfurther comprising adjusting an amount of one of the at least two bulkmaterials or powders according to a desired blend composition.
 5. Themethod of claim 1, further comprising determining whether the flow ofthe bulk material or powder is a dense-phase flow, a multi-phase flow,or a dilute phase flow based on the characteristic of the bulk materialor powder.
 6. A device comprising: a processor circuit; a memory circuitstoring commands, which, when executed by the processor circuit, causesthe device to perform a method comprising: receiving a first signal froma first optical computing device at a first location in a system forstoring and conveying materials; receiving a second signal from a secondoptical computing device at a second location in the system for storingand conveying materials, wherein the first and second signals resultfrom a light interacted with at least two bulk materials or powdersflowing in a transfer tube, and at least one of the first and secondsignals results from modifying the interacted light with an IntegratedComputational Element (ICE); determining, from the first signal and thesecond signal, a blend composition of the at least two bulk materials orpowders; and outputting instructions to adjust an amount of one of theat least two bulk materials or powders according to a desired blendcomposition.
 7. The device of claim 6, wherein the first location iswithin a pneumatic conveyor in the system for storing and conveyingmaterials.
 8. The device of claim 6, wherein the second location iswithin a pneumatic conveyor located downstream from the first locationin the system for storing and conveying materials.
 9. The device ofclaim 6, wherein the first location and the second location are axiallyoffset from each other along a pneumatic conveyor in the system forstoring and conveying materials.
 10. The device of claim 6, wherein thefirst location and the second location are offset along a directionsubstantially perpendicular to a direction of flow of a bulk material orpowder in a pneumatic conveyor of the system for storing and conveyingmaterials.
 11. A method comprising: receiving an output signal from eachof a plurality of optical computing devices disposed in separatelocations in a pneumatic conveyor flowing a bulk material or powder;processing each of the output signals from the plurality of opticalcomputing devices with a signal processor; determining a characteristicof the flow of bulk material or powder based on processing of the outputsignals; and modifying a physical parameter of the pneumatic conveyor inresponse to the value of the characteristic of the flow of bulk materialor powder, the physical parameter comprising at least one of a pipelength, a pipe diameter, or a pipe trajectory in the pneumatic conveyor.12. The method of claim 11, wherein at least two of the plurality ofoptical computing devices are disposed in different locations along thedirection of the flow of bulk material or powder, the method furthercomprising correlating in time the output signals from the at least twoof the plurality of optical computing devices in the signal processor,and determining a flow rate of the bulk material or powder.
 13. Themethod of claim 11, wherein determining a characteristic of the flow ofbulk material or powder comprises determining a flow profile in thepneumatic conveyor.
 14. The method of claim 11, wherein determining acharacteristic of the flow of bulk material or powder comprisesdetermining whether a flow of the bulk material or powder is asegregated flow or a homogeneous flow.
 15. The method of claim 11,wherein modifying a characteristic of the pneumatic conveyor comprisesmodifying at least one of a material feed rate or a differential airpressure in the pneumatic conveyor.
 16. The method of claim 11, whereindetermining a characteristic of the bulk material or powder comprisesdetermining at least partially a shape and a size of a layer of residualmaterial deposited inside the pneumatic conveyor.
 17. The method ofclaim 11, further comprising determining a difference in thecharacteristic of the flow of bulk material or powder at the differentlocations in the pneumatic conveyor.